Spur detection, cancellation and tracking in a wireless signal receiver

ABSTRACT

A method and device for processing spur components associated with a received wireless signal are disclosed. In one embodiment, the method includes first selecting a sub-band of a spectral band of the received signal. The selected sub-band is scanned, and a detection routine is executed to detect a spur within the scanned sub-band having a peak magnitude above a predetermined threshold. The spur frequency is determined, and the spur may be removed by a cancellation unit based on the determined frequency. The method also includes tracking the frequency of the spur to ensure continued suppression over time and under dynamic conditions.

TECHNICAL FIELD

The present embodiments relate generally to data communications, andmore particularly to methods and apparatus that provide spur detectionand cancellation.

BACKGROUND OF RELATED ART

Global navigation satellite systems (GNSS), such as the GlobalPositioning System (GPS), Galileo and the like, generally rely on aterrestrial navigation receiver to process signals from a satelliteposition system (“SPS signals”). The SPS signals are usually transmittedfrom transmitters fixed to space vehicles (SVs) to obtain pseudo-rangemeasurements from the terrestrial navigation receiver to thetransmitters.

In many instances, the terrestrial navigation receiver may need toovercome undesired radio frequency (RF) energy in the form ofradio-frequency-interference (RFI) or “spurs.” The spurs take the formof narrow-band frequency signals that may result from in-band orout-of-band noise sources.

One proposed method of handling spurs involves detecting the spurs andprogramming spur cancellation circuits to cancel the spurs. This may bean effective way to remove the spurs. However, over time the spurs mayexhibit changes in characteristics such as an offset in frequency orvariable strength and bandwidth.

SUMMARY

A method and device for processing spurs associated with a receivedwireless signal are disclosed. In one embodiment, the method includesselecting a sub-band of a spectral band of the received signal, scanningthe selected sub-band, and detecting, within the scanned sub-band, aspur having a peak magnitude above a predetermined threshold. Thefrequency of the spur is then determined. In some embodiments, the spurmay be removed based on the spur frequency. In some embodiments, thespur frequency may be tracked over time and under dynamic conditions.

BRIEF DESCRIPTION OF THE DRAWINGS

The present embodiments are illustrated by way of example and are notlimited by the figures of the accompanying drawings, where:

FIG. 1 illustrates one embodiment of a wireless system architecture;

FIG. 2 shows a block diagram illustrating one embodiment of theinterrelationship between the spur detector, spur tracker and spurcancellation unit employed in the system of FIG. 1;

FIG. 3 illustrates the spur detector of FIG. 1 in detail, in accordancewith one embodiment;

FIG. 4 shows a high-level flowchart illustrating a method of operationof the system of FIG. 1, in accordance with one embodiment;

FIG. 5 illustrates one embodiment of the estimation logic employed inthe spur cancellation unit of FIG. 1;

FIG. 6 illustrates one embodiment of the spur detector and spur trackerof FIG. 1;

FIG. 7 illustrates one embodiment of the mapping step of FIG. 4;

FIG. 8 illustrates one embodiment of the tracking step of FIG. 4; and

FIG. 9 illustrates one embodiment of overlapping frequency bands or binsfor multiple frequency bin tracking operations.

DETAILED DESCRIPTION

In the following description, numerous specific details are set forthsuch as examples of specific components, circuits, and processes toprovide a thorough understanding of the present disclosure. Also, in thefollowing description and for purposes of explanation, specificnomenclature is set forth to provide a thorough understanding of thepresent embodiments. However, it will be apparent to one skilled in theart that these specific details may not be required to practice thepresent embodiments. In other instances, well-known circuits and devicesare shown in block diagram form to avoid obscuring the presentdisclosure. The term “coupled” as used herein means connected directlyto or connected through one or more intervening components or circuits.Any of the signals provided over various buses described herein may betime-multiplexed with other signals and provided over one or more commonbuses. Additionally, the interconnection between circuit elements orsoftware blocks may be shown as buses or as single signal lines. Each ofthe buses may alternatively be a single signal line, and each of thesingle signal lines may alternatively be buses, and a single line or busmight represent any one or more of a myriad of physical or logicalmechanisms for communication between components. The present embodimentsare not to be construed as limited to specific examples described hereinbut rather to include within their scopes all embodiments defined by theappended claims.

More specifically, and referring generally to FIG. 1, a signalingenvironment 100 is shown that includes a portable electronic device,such as a mobile station 102 that receives wireless signals from varioustransmit sources 104, 106 and/or 130. In one embodiment, the mobilestation 102 may be a computing and/or communications device such as amobile telephone, a smart phone, a laptop computer, a tablet computer,and so forth. The mobile station 102 may perform and/or otherwisesupport various positioning and/or navigation functions (e.g., positionestimation, velocity estimation, time estimation, tracking, routing,location-based services, etc.) based, at least in part, on one or moresignals from a satellite positioning system (SPS). The mobile station102 may include a receiver 108 that interfaces with a spur detector 114,spur tracker 115 and signal processor 116. A variety of circuitry and/orsoftware enabling other capabilities 120 may be coupled to the signalprocessor 116.

Further referring to FIG. 1, the receiver 108 may include an RFfront-end 110 and a baseband processor 112. The RF front-end 110receives RF waveforms that are transmitted via one or more satellitepositioning system (SPS) transmitters 104. The baseband processor 112receives the output of the RF front-end 110 and converts the received RFsignals to baseband signals. The baseband processor 112 may interfacewith the signal processor 116 through a spur cancellation unit 118. Oneembodiment of a spur cancellation unit 118 may employ notch filters asdescribed below in further detail.

To address spur signal components that may be present in a receivedsignal, the spur detector 114 may operate in concert with the spurtracker 115 and spur cancellation unit 118. In one embodiment, the spurdetector 114 may detect one or more undesirable signals (e.g., acontinuous wave signal 107 transmitted via other transmitter 106) whichmay interfere with the reception of one or more desired signals (e.g.,SPS signal 105). The spur cancellation unit 118 coupled to the spurdetector 114 may be configured to cancel spurs caused by the undesirablesignals 107 from the received waveform. The spur tracker 115 may monitordetected spurs and periodically update stored information relating todynamic frequency characteristics in each spur (such as phase, frequencyand/or amplitude). This allows for a straightforward adaptive way todetect and cancel spurs over time and under changing environmentalconditions (such as reception conditions, proximity to interferingdevices, common spur frequencies, etc.). In FIG. 1, the solid linesbetween the spur detector 114, spur cancellation unit 118 and spurtracker 115 represent signal flow of input/output (I/O) samples, whilethe dashed lines represent the control signals, such as spur frequencyvalues.

By detecting, tracking, and cancelling the spurs, the receiver 108 thusgenerates filtered signal data that may be further processed and/orotherwise used by the signal processor 116 and/or the other capabilities120.

For example, the signal processor 116 may process the filtered data toestimate a position, location, range, velocity, and/or other informationthat may be beneficial in providing positioning or navigation servicesto a user. The other capabilities 120 may utilize the informationgenerated by the signal processor 116 to provide a displaying capabilitythat presents mapping or routing information to a user via an outputdevice (not shown), and/or a network interface capability that providescommunication between the mobile station 102 and one or more otherresources (devices) 132, via a communication link 131 with one or morewired and/or wireless networks 130.

In one embodiment, other resources (devices) 132 may be a server, acloud computing device, other suitable computing devices/services, orany combination thereof. The network 130 may be a telephone network, acellular network, a local area network, a wireless local area network,an intranet, the Internet, and so forth.

FIG. 2 illustrates one example of an interrelationship between the spurdetector 114, the spur tracker 115 and the spur cancellation unit 118.The spur cancellation unit 118 in one embodiment may take the form of adistributed set of notch filters SEC 202 a-202 n that receive an inputsignal “Input” and selectively pass portions of the input signal througha multiplexer 204 to a spur detection and tracking circuit (SDT) 206that corresponds to the spur detector 114 and spur tracker 115 ofFIG. 1. Each of the notch filters SEC 202 a-202 n may be programmed toexhibit a notch at an estimated or detected spur frequency so as tocancel the respective spur. In this example, the plurality of filtersmay provide the ability to track and cancel plural detected spurs.

One embodiment of spur detector 114 of FIG. 1 is illustrated as a spurdetector circuit 300 in FIG. 3. The spur detector circuit 300 mayinclude a mixer 302 that receives input samples at a rate of, forexample, 16 MHz from a digital front end (DFE output) (not shown). Themixer 302 also receives a mixer signal having a frequency that issynthesized from a master frequency F(k) fed to a numerically controlledoscillator (NCO) 304. The mixer signal frequency may be controlled viasoftware according to a search algorithm more fully described below.Varying the mixer frequency allows for varying corresponding spur searchwindows (in terms of frequency bands) for spur detection and tracking.

To achieve higher spur detection sensitivity and improved spur frequencyestimation precision, the mixed signal that is output from the mixer 302may be supplemented by an integrate and dump (I&D) unit 306 thatprovides a variable decimation or down sampling function. This is, ineffect, a form of low-pass filter that reduces the signal bandwidth inorder to look at a reduced portion of the signal spectrum. In oneembodiment, the variable decimation size may be represented by a valueof 128 and/or 32, such that the bin size can be calculated from therelationship:

${B_{f} = \frac{f_{s}}{2048\; L}},$where L is a decimation value, f_(s)=16.48 MHz is the samplingfrequency, and 2048 (8-bit input bit width) is the size of a fastFourier transform engine (FFT) 310 which is more fully described below.Based on the relationship above, for larger decimation values of L,finer FFT bin resolution may be attained at a cost of reduced searchrange.

Further referring to FIG. 3, the integrate and dump unit 306 feeds alevel shifter 308 that controls a programmable shift value n for the8-bit input bit width into the FFT 310. In one embodiment, a defaultvalue of n may be expressed as n=round(log₂√{square root over (L)}).Controlling the value of n allows for a trade-off between the spurdetection sensitivity and maximum spur power tolerance. Morespecifically, a larger value of n results in a higher spur powertolerance but at a cost of less detection sensitivity. Exemplary shiftvalues for n range from −2 to 5. In some embodiments, the level shifteroutput may be rounded to match the input size of the FFT 310. In oneembodiment, the FFT 310 may employ an 8-bit input width for a range of2048 points.

With continued reference to FIG. 3, in one embodiment, the FFT 310 feedsits output to a differential multiplier 312. The differential multiplier312 takes the FFT output and also receives a value from a memory 314that may be based on one or more previous FFT outputs. The differentialmultiplier 312 feeds its output to a coherent summer 316 having a secondmemory 318. The second memory 318 may accumulate the differentialmultiplication results, and may be implemented as one or more registers.Since the differential multiplication result is a complex number, it hasI (in-phase) and Q (quadrature phase) components. A peak index, or bestmatch, in terms of respective I and Q components for one of several spurdetection results may be provided along a path 317. The differentialmultiplier 312 and coherent summer 316 together may perform thefollowing function expressed by the relationship:

${{Z(i)} = {\sum\limits_{m = 1}^{M - 1}{{y\left( {m,i} \right)} \times {{conj}\left( {y\left( {{m - 1},i} \right)} \right)}}}},$where y(m,i) is the i-th frequency bin of the m-th FFT output, and Z(i)is the output of the differential summation over M−1 pairs. For example,if M=4, four samples are read in to form 3 pairs. In this way, the spurdetector circuit 300, in one mode, is capable of carrying out adifferential phase detection for highly accurate spur locationidentification.

In some instances, it may be desirable to utilize the output of the FFT310 directly, rather than carrying out the differential multiplicationand coherent summing. To allow for a selection between the direct outputmode and the multiplied/summed output mode, a selector 320 may beprovided. The selected output mode can generally depend on the desiredsensitivity for spur detection. A control signal CTL1 fed to theselector 320 may provide for software selection of the desired mode.

Further referring to FIG. 3, the selected FFT output (whether feddirectly or through the multiplier/summer) may be fed to an amplitudedetector 322 which evaluates the in-phase I (magnitude) and quadraturephase Q (phase) components of the FFT output to estimate the receivedsignal amplitude. In one embodiment, the amplitude may be estimated bythe relationship:max(|I|,|Q|)+floor(0.5*min(|I|,|Q|))

The amplitude value estimated by the amplitude detector 322 may then befed to a peak search engine 324 and an averaging engine 326. In oneembodiment, the peak search engine 324 may generate a peak valuerepresenting a magnitude parameter, and a peak index value that may bean integer from 0 to 2047. The averaging engine 326 may generate anaveraged magnitude over, for example, 2048 of the FFT sub-carriers. Withthese values, system software may calculate thepeak-to-average-power-ratio (PAPR) in terms of the peak value(magnitude)/mean value (magnitude) to determine if the correspondingfrequency is a spur.

In operation, the hardware and corresponding software of FIGS. 1-3 maycooperate with an intelligent software platform to employ search schemesthat detect, cancel and track spurs. Depending on the type of mobiledevice being operated, for example, the software platform may control asequence of operations to search for, detect, track and cancel spurs.FIG. 4 illustrates steps involved in one method of operation. As thereceiver 108 (FIG. 1) receives signals exhibiting a given spectral band,at step 400, a selected set of sub-bands of frequencies may be scannedby the spur detector 114, at step 402. The sub-band selection may bebased on a variety of criteria, including the desired sensitivity ofspur detection and the acceptable duration for spur detection. Thesensitivity criteria may be based on the signaling environment of thereceiver 108 and known reception conditions and other environmentalvariables (typical interfering devices nearby, common spur frequencies,etc.).

Once a spur is detected, at step 404, a determination may be madewhether the magnitude of the peak energy associated with the spur isgreater than a predetermined peak threshold, at step 406. If so, thespur cancellation unit 118 may be programmed to cancel the detected spurbefore the detection process continues with the other sub-bands. Thisenables the method to first address higher-magnitude spurs, which maybeneficially address aliasing issues associated with smaller spurshaving frequencies near the larger spurs. If the spur magnitude is belowthe threshold, operation may resume with scanning another sub-band, at402, and iteratively repeating the detection steps. If the spurmagnitude lies above the threshold, then the spur frequency may bedetermined through an estimation process, at step 408.

Once the spur frequency is identified, an evaluation may be carried outas to whether the spur is currently being tracked, at step 410. If not,a cancellation unit in the spur cancellation unit 118 may be programmed,at step 412, to remove the spur at the detected frequency so that theresulting signal is cleaned. If the spur is currently being tracked,then any changes in the frequency, phase or magnitude characteristics ofthe spur may be updated into system memory, at step 414. The searchalgorithm may then iterate to a new search sub-band or bin, at step 402.

FIG. 5 illustrates an estimation circuit, generally designated 500, thatforms a part of a further embodiment of a spur detection and trackingcircuit (SDT). Assuming that the spur is a single tone, its amplitudeand phase may be first estimated. The spur may then be reconstructed andsubtracted out. Although phase noise may smear the spur and create a“skirt” around the tone, the residual error after cancelling the singletone is negligible. This may be handled as an alternative to passing thesignal through a notch filter since it may be very difficult to build anarrow notch filter without distorting the signal when the notch isin-band.

Further referring to FIG. 5, an initial spur estimated frequency value,at 502, may be fed to a numerically controlled oscillator (NCO) 504. TheNCO may be used to generate the phase of the spur. In one embodiment,the maximum sample rate of the SEC circuit may be approximately 32 MHz.For a target frequency error of 0.01 Hz (i.e. 3.6 degrees of phase errorin 1 second), one embodiment may utilize 32 bits. The spur frequency maybe signed and may be limited in frequency to no greater than half thesample frequency.

To achieve a clean cancellation (where a residual is less than −130dBm), accurate estimations of the spur amplitude and phase may be made.The frequency from the NCO 504 may be passed to a sine/cosine (sin/cos)table 506. The resulting spur phasor may then be conjugated at conjugateblock (conj) 508, and the conjugate multiplied with the spur in theincoming signal, at multiplier 510. The output of the multiplier 510 maybe expressed by the relationship:

$\begin{matrix}{{y(t)} = {{{acos}\left( {{\omega\; t} + \theta} \right)}{\exp\left( {{- {j\omega}}\; t} \right)}}} \\{= {{a/2}\left( {{\exp\left( {j\left( {\omega + \theta} \right)} \right)} + {\exp\left( {- {j\left( {{\omega\; t} + \theta} \right)}} \right)}} \right){\exp\left( {{- {j\omega}}\; t} \right)}}} \\{= {{a/2}\left( {{\exp({j\theta})} + {\exp\left( {- {j\left( {{2\omega\; t} + \theta} \right)}} \right)}} \right)}}\end{matrix}$With continued reference to FIG. 5, the output of the multiplier 510 maythen be fed to an averaging circuit 512, and averaged over a large blocksize, such as N=4096 samples. As a result, the second term of themultiplier output diminishes, and the result represents the amplitudeand phase of the spur, or aexp(jθ). To cancel the spur, the complexvalue may be fed to a cancellation sub-module 515 that includes a gate514 and multiplier 516. A box filter (DUMP) 518 is coupled to the gate514. The complex value is multiplied with the spur phasor, and the realpart obtained, a cos(ωt+θ) by a real part extraction circuit 519. Thisvalue represents the reconstructed spur, which may then be fed to asumming circuit 520 to cancel out the spur in the incoming signal.

FIG. 6 illustrates a spur detection and tracking circuit, generallydesignated 600, that may cooperate with the estimation circuit 500 ofFIG. 5 to provide enhanced sensitivity for detecting low-power spurs.The enhanced sensitivity may be realized through use of a differentialdetection technique that evaluates two outputs from an FFT that havedifferent phases associated with them. The difference in phasecorresponds to the frequency width of the tone.

Further referring to FIG. 6, the output from the box filter 518 (FIG. 5)may be fed to the input of another filter 602 that generates an averagedvalue of x(I) over L repetitions of estimation. This may improve thesignal to noise ratio of the estimate, and spur detection/trackingsensitivity. The output y may be calculated by the relationship

${y(m)} = {{\frac{1}{L}{\sum\limits_{l = {{{({m - 1})}L} + 1}}^{m\; L}{x(l)}}} \approx {\frac{1}{NL}{\sum\limits_{n = {{{({m - 1})}{NL}} + 1}}^{m\;{NL}}{\mathbb{e}}^{j{({{2{\pi{({f_{est} - f_{spur}})}}n\; T_{s}} + \theta})}}}}}$

The output of the filter 602 may then be fed to a differentialmultiplier 604. The differential multiplier takes the direct output anda delayed version of the output from a delay element 606 and maygenerate a differential product. The result is a computation of aself-correlation of the spur estimate, and an angle extraction thatcontains information of the spur frequency error. Further, thedifferential product value eliminates any unknown phase componentassociated with the differential signal components.

To achieve a better signal-to-noise ratio, the output of thedifferential multiplier 604 may be fed to a differential summation andaveraging circuit 608. The circuit may be controlled by a factor M thatmay be generated by software. The output may be calculated by theequation:

${z(k)} = {{\frac{1}{M}{\sum\limits_{m = 1}^{M}{{y(m)}{y^{*}\left( {m - 1} \right)}}}} \approx {\mathbb{e}}^{j\; 2{\pi{({f_{est} - f_{spur}})}}N\; L\; T_{s}}}$By calculating the angle of z(k), one can determine an estimated spurfrequency error f_(e) as

$f_{e} = {{f_{est} - f_{spur}} \approx \frac{{angle}\left( {z(k)} \right)}{2\pi\; N\; L\; T_{s}}}$With the determined spur frequency error, tracking the spur may becarried out by updating an estimated spur frequency based on the currentfrequency error.

With continued reference to FIG. 6, a register 610 may receive theoutput of the differential summation and averaging circuit 608. In oneembodiment, the register 610 triggers an interrupt signal to inform thesoftware of the spur frequency identification. The output from theregister 610 may be used directly as a maximum correlation value, at612, and may be fed to a peak detection circuit 616 for respective peakI (in-phase) and Q (quadrature phase) magnitude values. The peakdetection circuit 616 may feed the output from the register 610 to anaveraging circuit 614 to generate average correlation values.

As noted above with respect to the steps of FIG. 4, the search algorithmfor mapping detected spurs may involve iteratively scanning multiplewindows or bins for spurs. One embodiment may prioritize the detectionof high-power spurs first in order to avoid aliasing effects. High-powerspurs may need less detection sensitivity associated with them, so awider band of frequencies may be scanned for a given search. Incontrast, low-power spurs may need higher detection sensitivity, and soa narrower band of frequencies may be scanned accordingly.

FIG. 7 illustrates a more detailed series of steps involved in searchingfor the spurs of interest. The method begins by first setting a counterto a default value to track a number of search iterations or mappingruns, at 702. The number of mapping runs for the algorithm may be one,or a higher value depending on the application. Previously identifiedspur frequencies may then be masked to minimize the chance ofre-detection, at 704. For one embodiment, the masking may involvedisabling a narrow frequency band centered on the detected spur.

Further referring to FIG. 7, after masking, a bin of interest (BOI) maybe searched, at 706. The bin of interest may involve a pre-programmedset of sub-band parameters such as, for example, 8 MHz for an initialstrong-power search mapping, followed by 2 MHz for a medium-powermapping, and 64 KHz for weak-power mapping when the frequency of thespur is roughly known. During the search stage, according to a measuredsignal power, multiple numbers of candidate frequencies with top powermay be recorded and sent to a verify stage for further confirmation ofdetection.

Upon receiving spur candidates, a verification may be carried out, at708 that involves examining the spur candidates one-by-one through ananalysis of a peak-to-average-power-ratio (PAPR) of the sub band and apeak power value of the sub band, at 710. Verification may involvereducing the search window for a given spur, and increasing thesensitivity to confirm that the detected spur is not an anomaly. Duringthe verification, the searched spurs may only be deemed valid if (1) thePAPR of the sub-band containing the spurs is higher than a certainthreshold, denoted by R, and (2) the power of the detected spur ishigher than a threshold P_(spur). Both thresholds R and P_(spur) may beprogrammed values. Also, the verification is executed for a maximumnumber of spurs, K_(max), that is dictated by the number of spurcancellation and tracking units in the system.

Further referring to FIG. 7, after the candidate spurs are verified andexceed the power threshold, the detection circuit may report a findingof a possible spur, at 712. A spur counter value may then beincremented, at 714, and a determination may be made as to whether thenumber of detected spurs exceeds the maximum value K_(max), at 716. Ifthe threshold is not exceeded, no report is made, and operation mayiterate back to the masking step 704. If the count value exceeds themaximum count K_(max), then the results of the search routine may beoutput to the spur cancellation unit, at 718 such that the detected spurfrequencies are identified for cancellation by the notch filtercircuitry.

Referring to FIG. 8, the spur detection and tracking circuit may employa counter to record the tracking history. The process begins by settingthe counter to a default value, such as 1, at 802. A current estimationfrequency f_(est)(k) may be set, at 804. The outputs of the differentialsumming and averaging circuit corresponding to the frequency estimatesmay then be identified as z(k), at 806. A determination may then be madeas to whether the count value is at a maximum value K_(max), at 808. Ifnot, then the counter may be incremented, at 809, and the frequencyre-estimated, at 804. If the counter value exceeds K_(max), then afurther determination may be made, at 810, as to whether the maximumvalue of the estimated frequency z(k) is higher than a predeterminedthreshold Tr. If so, then the tracking may be viewed as successful, andthe counter reset, at 812, and the frequency estimation pool f_(est)(k)updated, at 814.

Further referring to FIG. 8, if the maximum value of the estimatedfrequency z(k) is less than the threshold Tr, then the current trackingcycle may have failed, and the counter is incremented, at 816. Thecounter value may then be evaluated, at 818, to determine whether it ishigher than a predetermined count value Cmax. If so, the counteroverflow is triggered and the tracking may be viewed as failed, with areport of a loss of tracking generated at 820. If the counter is nothigher than Cmax, then the frequency estimation pool may be updated, at814.

Referring now to FIG. 9, a result of the method described in FIG. 8 maybe illustrated graphically, with the estimated frequency fest (thecenter of the frequency bin) bounded by two nulls at(f_(est)−0.6/NLT_(s)) and (f_(est)+0.6/NLT_(s)). As explained above, inan effort to increase the detection and tracking ranging of thedetection and tracking circuitry, a plurality n*K_(max) of bins may besearched, spanning from the estimated frequency f_(est). In someembodiments, as shown in FIG. 9, the bins may be overlapped by aspecified percentage, such as 40-50% to achieve desired detectionsensitivity. In some embodiments, the value of n*K_(max) may be an oddvalue, and the middle bin may be centered at the estimated frequencyf_(est).

In one embodiment, a number n of bins may be tracked, spanning from anestimated frequency f_(est). In some instances, the bins may beoverlapped to achieve better detection sensitivity. For one example,each of the n frequency bins may be spaced apart by a predefined value(based on the reciprocal of a total coherent integration time generatedby a differential summation circuit, described below). This may increasethe detection and tracking range of the circuit. In one example, a 40%overlap may be employed, resulting in each of the n frequency binshaving a

$\frac{1}{N\; L\; T_{s}}$Hz null-to-null width, and spaced

$\frac{0.6}{N\; L\; T_{s}}$Hz apart. The value of n may be an odd value, and the middle bin may becentered at f_(est).

In one specific example, where n=3, three frequency estimates arechecked:

$\left\{ {{f - \frac{0.6}{N\; L\; T_{s}}},f_{est},{f_{est} + \frac{0.6}{N\; L\; T_{s}}}} \right\},$and the corresponding outputs of the differential summation and averagecircuit calculated, denoted by z(k), k=1, 2, . . . , n_(max). Themultiple frequency estimates are referred to as a frequency estimationpool centered at f_(est).

Those skilled in the art will appreciate that the proposed schemes thusprovide detection and tracking of spur frequencies in an efficient andaccurate manner.

In the foregoing specification, the present embodiments have beendescribed with reference to specific exemplary embodiments thereof. Itwill, however, be evident that various modifications and changes may bemade thereto without departing from the broader scope of the disclosureas set forth in the appended claims. The specification and drawings are,accordingly, to be regarded in an illustrative sense rather than arestrictive sense.

What is claimed is:
 1. A method of processing spur components associatedwith a wireless signal, the method comprising: selecting a sub-band of areceived signal; determining a first Fast Fourier Transform (FFT) based,at least in part, on the selected sub-band, the first FFT including anumber of frequency bins; determining a first differential product foreach frequency bin of the first FFT based, at least in part, on thefirst FFT and a complex conjugate of a second FFT based, at least inpart, on the selected sub-band; and determining a spur frequency based,at least in part, on the first differential product.
 2. The method ofclaim 1, further comprising: cancelling a spur based on the determinedspur frequency; and tracking the determined spur frequency over time. 3.The method of claim 2, wherein the tracking comprises: storing initialinformation associated with the spur; detecting any frequency changesassociated with the spur; and updating the initial information toreflect the detected frequency changes.
 4. The method of claim 1,wherein the first differential product is a complex product of the firstFFT and the complex conjugate of the second FFT.
 5. The method of claim1, wherein the second FFT is determined after the first FFT isdetermined.
 6. The method of claim 1, wherein determining the spurfrequency comprises: determining a coherent sum for each frequency binof the first FFT based, at least in part, on the first differentialproduct associated with each frequency bin and a second differentialproduct associated with each frequency bin; and selecting the spurfrequency based, at least in part, on an average coherent sum and a peakcoherent sum, wherein the average coherent sum is an average value ofthe coherent sums associated with each frequency bin and the peakcoherent sum is a largest coherent sum selected from the coherent sumsassociated with each frequency bin.
 7. The method of claim 6, whereinthe coherent sum is a complex sum of the first differential product andthe second differential product, and the second differential product isbased, at least in part, on the second FFT and a complex conjugate of athird FFT based, at least in part, on the selected sub-band.
 8. Themethod of claim 7, wherein the third FFT is determined after the firstFFT and the second FFT are determined.
 9. The method of claim 6, whereinthe spur frequency is associated with the peak coherent sum that isgreater than a threshold.
 10. The method of claim 6, wherein the spurfrequency is associated with the peak coherent sum that exceeds theaverage coherent sum by at least a threshold amount.
 11. A receiver,comprising: a radio frequency (RF) front end to receive a signal; and abaseband processor to: select a sub-band of the received signal;determine a first Fast Fourier Transform (FFT) based, at least in part,on the selected sub-band, the first FFT including a number of frequencybins; determine a first differential product for each frequency bin ofthe first FFT based, at least in part, on the first FFT, and a complexconjugate of a second FFT based, at least in part, on the selectedsub-band, wherein the second FFT is determined after the first FFT isdetermined; and determine a spur frequency based, at least in part, onthe first differential product.
 12. The receiver of claim 11, whereinthe baseband processor is to determine the frequency spur by:determining a coherent sum for each frequency bin of the first FFTbased, at least in part, on the first differential product associatedwith each frequency bin and a second differential product associatedwith each frequency bin; and selecting the spur frequency based, atleast in part, on an average coherent sum and a peak coherent sum,wherein the average coherent sum is an average value of the coherentsums associated with each frequency bin and the peak coherent sum is alargest coherent sum selected from the coherent sums associated witheach frequency bin.
 13. The receiver of claim 12, wherein the coherentsum is a complex sum of the first differential product and the seconddifferential product.
 14. The receiver of claim 12, where the spurfrequency is associated with the peak coherent sum that is greater thana threshold.
 15. The receiver of claim 12, where the spur frequency isassociated with the peak coherent sum that exceeds the average coherentsum by at least a threshold amount.
 16. A device for processing spurcomponents associated with a wireless signal, the device comprising:means for selecting a sub-band of a received signal; means fordetermining a first Fast Fourier Transform (FFT) based, at least inpart, on the selected sub-band, the first FFT including a number offrequency bins; means for determining a first differential product foreach frequency bin of the first FFT based, at least in part, on thefirst FFT and a complex conjugate of a second FFT based, at least inpart, on the selected sub-band, wherein the second FFT is determinedafter the first FFT is determined; and means for determining a spurfrequency based, at least in part, on the first differential product.17. The device of claim 16, further comprising: means for cancelling aspur based on the determined spur frequency; and means for tracking thedetermined spur frequency over time.
 18. The device of claim 16, whereinmeans for determining the spur frequency further comprises: means fordetermining a coherent sum for each frequency bin of the first FFTbased, at least in part, on the first differential product associatedwith each frequency bin and a second differential product associatedwith each frequency bin, wherein the coherent sum is a complex sum ofthe first differential product and the second differential product; andmeans for selecting the spur frequency based, at least in part, on anaverage coherent sum and a peak coherent sum, wherein the averagecoherent sum is an average value of the coherent sums associated witheach frequency bin and the peak coherent sum is a largest coherent sumselected from the coherent sums associated with each frequency bin. 19.The device of claim 18, wherein the spur frequency is associated withthe peak coherent sum that is greater than a threshold.
 20. The deviceof claim 18, wherein the spur frequency is associated with the peakcoherent sum that exceeds the average coherent sum by at least athreshold amount.